Junior Engineer
Ford Motor Company
full-time
Posted on:
Location Type: Hybrid
Location: Chennai • India
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Job Level
Tech Stack
About the role
- Responsibilities **
- Design and build GCP data driven solutions for enterprise data warehouse and data lakes **
- Design and implement scalable data architectures on GCP, including data lakes, warehouses, and real-time processing systems.**
- Utilize ML Services like Vertex AI.**
- Develop and optimize ETL/ELT pipelines using tools like Python, SQL, and streaming technologies (e.g., Kafka, Apache Airflow).**
- Architect Historical and Incremental Loads and Refine Architecture on an ongoing basis**
- Manage and optimize data storage, partitioning, and clustering strategies for high performance and reliability, utilizing services such as BigQuery, Spark, Pub/Sub, and Object Storage.**
- Collaborate with data scientists, Data engineers, and other stakeholders to understand data needs and deliver solutions aligned with business objectives, security, and data governance.**
- Automate infrastructure and deployments using Infrastructure as Code (IaC) using tools like Terraform and CI/CD practices (e.g., Tekton) to ensure reliability and scalability.**
- Operationalize machine learning models by building data infrastructure and managing structured and unstructured data, supporting AI/ML/LLM workflows, including data labeling, classification, and document parsing.**
- Monitor and troubleshoot data pipelines and systems to identify and resolve issues related to performance, reliability, and cost-effectiveness.**
- Document data processes, pipeline designs, and architecture, contributing to knowledge transfer and system maintenance.**
Requirements
- **Qualifications and Skills **
- - Must have -
- - Professional GCP - Data Engineer Certification.
- - 2 + years coding skills in Java/Python and Terraform.
- - 2+ years’ experience
- - Experience in working with Agile and Lean methodologies.
- - GCP Expertise: Strong proficiency in GCP services, including BigQuery, Dataflow, Dataproc, Data Fusion, Air Flow, Pub/Sub, Cloud Storage, Vertex AI, Cloud Functions, and Cloud Composer, GCP based Big Data deployments (Batch/Real-Time) leveraging Big Query, Big Table
- - Programming & Scripting: Expert-level skills in Python and SQL are essential. Familiarity with languages like Scala or Java can also be beneficial, especially for working with tools like Apache Spark.
- - Data Engineering Fundamentals: Solid understanding of data modeling, data warehousing concepts, ETL/ELT processes, and big data architecture, Designing pipelines and architectures for data processing.
- - Big Data Technologies: Experience with technologies like Apache Spark, Apache Beam, and Kafka is often required.
- - DevOps & MLOps: Knowledge of DevOps methodologies, CI/CD pipelines, and MLOps practices, including integrating data pipelines with ML workflows.
- - Security & Compliance: Expertise in implementing Identity and Access Management (IAM) policies, ensuring data encryption, and adhering to data privacy regulations.
- - Analytical & Problem-Solving Skills: Demonstrated ability to analyze complex datasets, identify trends, debug issues, and optimize systems for performance and cost efficiency.
- - Communication & Collaboration: Excellent communication and teamwork skills, with the ability to collaborate effectively with technical and non-technical stakeholders in agile environments.
- - Experienced in Visualization Tool – Qlik, Looker Studio, Power BI
- - Knowledge of VBA, will be a plus
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
GCPPythonSQLTerraformApache SparkKafkaETLELTData WarehousingData Modeling
Soft Skills
Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration SkillsAgile MethodologiesTeamworkAdaptabilityAttention to DetailCritical ThinkingTime Management
Certifications
GCP Data Engineer Certification